System and method for detecting scan irregularities at self-checkout terminals

ABSTRACT

A system for detecting a scan irregularity in scanning process during check-out at a retail store, includes an image receiving module for receiving a video stream of a scanning zone, an image processing module for detecting visual scan intervals in image frames of the video stream, and a decision module. The decision module is configured to process each detected visual scan interval, wherein a processed visual scan interval includes a valid scan action, wherein the valid scan action is a user action performed for scanning an item. The decision module is further configured to detect a scan irregularity in the check-out process, wherein the scan irregularity occurs when an item identified for scanning in a processed visual scan interval is absent in a list of scanned items generated by the scanner during corresponding interval, and provide an alert regarding the scan irregularity at a user computing device.

TECHNICAL FIELD

The present disclosure relates generally to self-checkout terminals in aretail store, and more specifically, to systems to generate an alert ifthere is a scan irregularity in visual scan detection.

BACKGROUND

Self-checkout machines provide a mechanism for customers to processtheir own purchases from a retailer. They are an alternative to thetraditional cashier-staffed checkout. The customer performs the job ofthe cashier themselves, by scanning and applying payment for the items.In a typical self-checkout system, the customer is required to scan eachitem against a scanner, and then do the requisite payment.

However, a customer may have little or no training in the operation of aself-service checkout terminal, and may make errors when checking outtheir items. The customer may unintentionally miss out some items whilescanning, and may move out of the store without making requisitepayment. Further, shop-lifting is a major disadvantage associated withself-checkout stores. For example, a customer may not scan some itemsintentionally, and put the unscanned items in their shopping cart, andmay move out of the store without making full payment. As a result, theself-check out stores may incur huge losses. Therefore, the currentself-check out stores may still require a high number of personnel orstore operators for preventing theft and unauthorized picking-up ofitems.

Therefore, in light of the foregoing discussion, there exists a need fora method and a system that detects scan irregularities in aself-checkout stores, that generates an alert when there is a mismatchbetween the products present in a shopping basket of the user, and ascanned list of items generated by the scanner, and that overcomes theaforementioned drawbacks associated with existing self-checkout systems.

SUMMARY

According to a first aspect of the present disclosure, there is provideda system for detecting a scan irregularity in scanning of one or moreitems by a user, during a check-out process at a retail store. Thesystem may include an image receiving module configured to receive avideo stream of a scanning zone in real-time from at least one videocamera, wherein the scanning zone is a region in a field of view of ascanner of the retail store. The system may further include an imageprocessing module configured to process each image frame of the videostream for detecting one or more visual scan intervals in one or moreimage frames, wherein the visual scan interval is a time interval duringwhich an item is identified in the scanning zone for scanning by thescanner. The system may further include a decision module configured toprocess each detected visual scan interval based on a set of pre-definedrules, wherein a processed visual scan interval includes a valid scanaction, wherein the valid scan action is a user action performed forscanning an item, detect a scan irregularity in the check-out process,wherein the scan irregularity occurs when an item identified forscanning in a processed visual scan interval is absent in a list ofscanned items generated by the scanner during corresponding interval,and provide an alert regarding the scan irregularity at a user computingdevice.

According to a second aspect of the present disclosure, there isprovided a method for detecting a scan irregularity in scanning of oneor more items by a user, during check-out process at a retail store. Themethod may include receiving a video stream of a scanning zone inreal-time from at least one video camera, wherein the scanning zone is aregion in a field of view of a scanner of the retail store. The methodmay further include processing each image frame of the video stream fordetecting one or more visual scan intervals in one or more image frames,wherein the visual scan interval is a time interval during which an itemis identified in the scanning zone for scanning by the scanner. Themethod may further include processing each detected visual scan intervalbased on a set of pre-defined rules, wherein a processed visual scaninterval includes a valid scan action, wherein the valid scan action isa user action performed for scanning an item. The method may furtherinclude detecting a scan irregularity in the check-out process, whereinthe scan irregularity occurs when an item identified for scanning in aprocessed visual scan interval is absent in a list of scanned itemsgenerated by the scanner during corresponding interval. The method mayfurther include providing an alert regarding the scan irregularity at auser computing device.

According to a third aspect of the present disclosure, there is provideda computer programmable product for detecting a scan irregularity inscanning of one or more items by a user, during check-out process at aretail store. The computer programmable product includes a set ofinstructions, the set of instructions when executed by a processorcauses the processor to receive a video stream of a scanning zone inreal-time from at least one video camera, wherein the scanning zone is aregion in a field of view of a scanner of the retail store, process eachimage frame of the video stream for detecting one or more visual scanintervals in one or more image frames, wherein the visual scan intervalis a time interval during which an item is identified in the scanningzone for scanning by the scanner, process each detected visual scaninterval based on a set of pre-defined rules, wherein a processed visualscan interval includes a valid scan action, wherein the valid scanaction is a user action performed for scanning an item, detect a scanirregularity in the check-out process, wherein the scan irregularityoccurs when an item identified for scanning in a processed visual scaninterval is absent in a list of scanned items generated by the scannerduring corresponding interval, and provide an alert regarding the scanirregularity at a user computing device.

Various embodiments of the present disclosure provide a system andmethod that detects scan irregularities in a self-checkout stores, thatgenerate an alert when there is a mismatch between the products presentin a shopping basket of the user, and a scanned list of items generatedby the scanner.

It will be appreciated that features of the present disclosure aresusceptible to being combined in various combinations without departingfrom the scope of the present disclosure as defined by the appendedclaims.

BRIEF DESCRIPTION OF THE DRAWINGS

The summary above, as well as the following detailed description ofillustrative embodiments, is better understood when read in conjunctionwith the appended drawings. For the purpose of illustrating the presentdisclosure, exemplary constructions of the disclosure are shown in thedrawings. However, the present disclosure is not limited to specificmethods and instrumentalities disclosed herein. Moreover, those in theart will understand that the drawings are not to scale. Whereverpossible, like elements have been indicated by identical numbers.

Embodiments of the present disclosure will now be described, by way ofexample only, with reference to the following diagrams wherein:

FIG. 1 illustrates a retail environment, wherein various embodiments ofthe present disclosure can be practiced;

FIG. 2 illustrates a system for generating an alert when there is a scanirregularity in visual scan detection in the retail environment, inaccordance with an embodiment of the present disclosure; and

FIG. 3 is a flowchart illustrating a method for generating an alert whenthere is a scan irregularity in visual scan detection in the retailenvironment, in accordance with an embodiment of the present disclosure.

In the accompanying drawings, an underlined number is employed torepresent an item over which the underlined number is positioned or anitem to which the underlined number is adjacent. A non-underlined numberrelates to an item identified by a line linking the non-underlinednumber to the item. When a number is non-underlined and accompanied byan associated arrow, the non-underlined number is used to identify ageneral item at which the arrow is pointing.

DETAILED DESCRIPTION OF EMBODIMENTS

The following detailed description illustrates embodiments of thepresent disclosure and ways in which they can be implemented. Althoughsome modes of carrying out the present disclosure have been disclosed,those skilled in the art would recognize that other embodiments forcarrying out or practicing the present disclosure are also possible.

Referring to FIG. 1, there is shown a retail environment 100, whereinvarious embodiments of the present disclosure can be practiced. Theretail environment 100 includes first through third self-checkoutterminals 102 a to 102 c (hereinafter collectively referred to asself-checkout terminals 102), and a central control unit 104,communicatively coupled to each other through a communication network106.

The communication network 106 may be any suitable wired network,wireless network, a combination of these or any other conventionalnetwork, without limiting the scope of the present disclosure. Fewexamples may include a Local Area Network (LAN), wireless LANconnection, an Internet connection, a point-to-point connection, orother network connection and combinations thereof. In an example, thenetwork may include a mobile communication network, for example, 2G, 3G,4G, or 5G mobile communication network. The communication network may becoupled to one or more other networks, thereby providing couplingbetween a greater number of devices. Such can be the case, for example,when networks are coupled together via the Internet.

Each self-checkout terminal 102 a to 102 c, for example, the firstcheck-out terminal 102 a is equipped with a first scanner 108 forenabling a user to scan one or more items themselves, and a first userdisplay 110 for enabling a user to make requisite selection and paymentof one or more items. In an example, the first scanner 108 may be a barcode scanner for scanning bar code of an item, for identifying the itemthereof. Preferably, the first scanner 108 is a stationary wall ortable-mounted scanner, designed for check-out counters of supermarkets,and other retail stores, for scanning items placed in a scanning zone.In the context of the present disclosure, the scanning zone is an areain front of the first scanner 108 where the user brings up the items forscanning for the purpose of buying of those items.

Further, each self-checkout terminal 102 a to 102 c may be surrounded byone or more overhead video cameras for capturing scanning zone of eachself-checkout terminal 102 a to 102 c, for example, the firstself-checkout terminal 102 a is surrounded by a first video camera 112.The first video camera 112 is configured to continuously capture a videoof the scanning zone, in order to facilitate detection of a scanirregularity due to a mismatch in the items brought up for scanning bythe user, and the actual items scanned by the first scanner 108.

The first user display 110 may be a touch-based display configured toreceive and display one or more instructions. Few examples may include,but are not limited to, Liquid Crystal Displays (LCD) devices, LightEmitting Diode (LED)-based displays, Organic LED (OLED)-based displaysdevices, and micro OLED-based display devices.

In an example, the first check-out terminal 102 a includes a processor(not shown) communicatively coupled to the first scanner 108 and thefirst user display 110, for recording scanning of one or more items bythe first scanner 108, and providing instructions on the first userdisplay 110 for payment of one or more scanned items. Throughout thepresent disclosure, the term ‘processor’ relates to a computationalelement that is operable to respond to and processes instructions thatdrive respective self-checkout terminal 102 a to 102 c. Optionally, theprocessor includes, but is not limited to, a microprocessor, amicrocontroller, a complex instruction set computing (CISC)microprocessor, a reduced instruction set (RISC) microprocessor, a verylong instruction word (VLIW) microprocessor, or any other type ofprocessing circuit. Furthermore, the term “processor” may refer to oneor more individual processors, processing devices and various elementsassociated thereof.

Each of the second and third check-out terminals 102 b and 102 c aresimilar to the first check-out terminal 102 a in terms of constructionand functionality, therefore, they have not been explained herein againfor the sake of brevity.

The central control unit 104 is communicatively coupled to eachself-checkout terminal 102 a to 102 c for controlling and managing theiroperations thereof. In an embodiment of the present disclosure, thescanners of each self-checkout terminal 102 a to 102 c arecommunicatively coupled to the central control unit 104 to record thescanned content in a memory of the central control unit 104, for furtherprocessing. Further, in another embodiment of the present disclosure,the video cameras present in the retail store environment 100 arecommunicatively coupled to the central control unit 104.

The central control unit 104 may include a system 114 for detecting amismatch in the items brought up for scanning in the scanning zone, andthe actual items scanned by corresponding scanner in the retailenvironment 100. Throughout the present disclosure, the term ‘system 114relates to a structure and/or module that include programmable and/ornon-programmable components configured to store, process and/or shareinformation. Optionally, the system 114 includes any arrangement ofphysical or virtual computational entities capable of enhancinginformation to perform various computational tasks. In an example, thesystem 114 may include components such as memory, a processor, a networkadapter and the like, to store, process and/or share information withother computing components.

FIG. 2 illustrates the system 114 for generating an alert when there isa scan irregularity in visual scan detection in the retail environment100, in accordance with an embodiment of the present disclosure. In thecontext of the present disclosure, “the scan irregularity” takes place,when there is a mismatch between items brought for scanning in ascanning zone by a user, and a list of scanned items generated bycorresponding scanner. The system 114 may be implemented at the controlunit 104, or at each self-check out terminal 102, or at both.

The system 114 includes an image receiving module 201 for receivingimages captured by one or more video cameras of the retail environment100, an image processing module 202 for processing the captured imagesto detect visual scan intervals, and a decision module 204 for detectingvalid scan intervals, and generating an alert in the event of a mismatchbetween item brought up for scanning, and actual items scanned bycorresponding scanner of the retail environment 100.

Referring back to FIG. 1, the ‘scan action’ is referred to as a useraction when the user brings up the item for scanning in the scanningzone of the first scanner 108, but it may or may not be successfullyscanned by the first scanner 108. In an example, a user may bring up anitem in the scanning zone of the first scanner 108, but the user mayhold the item in such a way that the bar code of the item may not bevisible to the bar code scanner 108. In such case, the user may put theitem in their shopping bag after performing the scan action, but inreality, it may not be scanned by the first scanner 108, and the usermay not receive a bill for that item. Therefore, detection of scanactions in image frames captured by the video cameras, are crucial indetermining one or more scan irregularities in the items scanned byscanners in the retail environment 100.

Referring again to FIG. 2, the image processing module 202 includes oneor more feature extraction modules that are used to extract featuresfrom a current image frame received by the image receiving module 201,that indicate the occurrence of the scan action within the current imageframe. The features may be designed in accordance with the action to bedetected. In the context of the present disclosure, the image processingmodule 202 includes a skin tone detector 206, a motion detector 208, anda key-point detector 210.

The skin tone detector 206 is configured to extract the percentage ofskin pixels in the current image frame relative to the previous imageframe with the intention to determine if there is a hand involved in ascan action. In the context of the present disclosure, an image pixel islabelled as a skin pixel if the image pixel is found to have a colorsimilar to the color of human skin. While scanning a product, usuallythe hand of the customer in present in the scanning zone, so an increasein percentage of skin pixels in the current image frame may indicate ascan action. The skin tone detector 206 receives a current image frameas an input, and generates a binary map indicating whether skin tone isbeing detected or not in the current image frame. In an embodiment ofthe present disclosure, the skin pixel percentage with respect to theforeground pixels have to be smaller than a pre-defined skin pixelthreshold value in each image frame. This is done in order to limit thefalse positives due to the passage of empty hands in the scanning area.

The motion detector 208 is configured to extract the percentage ofmotion pixels in the current image frame relative to the previous imageframe with the intention to determine if there is motion involved in ascan action. In the context of the present disclosure, a current imagepixel is labelled as a motion pixel if a motion has been detected in thecurrent image pixel with respect to a previous image pixel. Whilescanning a product, usually the hand of the customer moves in thescanning zone, so a detected motion in the video frame, can indicate ascan action. In an embodiment of the present disclosure, the motiondetector 204 receives a current image frame as an input, and generates abinary map indicating whether motion is being detected or not in thecurrent image frame.

The key-point detector 210 is configured to indicate the presence of anobject in the scanning zone. While scanning a product, usually when anew object enters into the scanning zone, the number of key-points wouldincrease due to the new geometrical form (the product) that is presentin the scene, and due to the textures that cover the product and whichcan create new corner points. In an embodiment of the presentdisclosure, the key-point detector 208 receives a current image frame asan input and generates a set of key-points as an output. Usually, a highnumber of key-points is associated with a scan action. A threshold onthe temporal evolution of the number of key-points present in thescanning zone provides an estimate of a visual scan interval. In thecontext of the present disclosure, the visual scan interval of a productis the time interval when the product was present in the scanning zone.In an example, if the product was present from 10:00 am to 10:00:02 amin the scanning zone, then the visual scan interval of the product is 2seconds.

The system 114 further includes a decision module 204 that is configuredto decide if a detected visual scan interval is valid, i.e. it includesa scan action or not. The decision module 204 is further configured todetermine whether the detected visual scan interval includes a scanaction or not, based on one or more pre-defined rules, in order toregularize the detected scan intervals, cope with certainsynchronization delays, and prevent eventual misclassifications.

According to a first pre-defined rule, the decision module 204 isconfigured to set a pre-defined range of scan interval, and discard thevisual scan intervals that are too small with respect to the pre-definedthreshold size, or are too big with respect to the pre-defined thresholdsize. In an embodiment of the present disclosure, the pre-definedthreshold size may correspond to a normal speed of the human hand.

According to a second pre-defined rule, the decision module 204 isconfigured to set a pre-defined threshold first distance betweenconsecutive visual scan intervals, and merge the visual scan intervalsthat are close with respect to the pre-defined threshold first distance.In an example, if the pre-defined threshold distance is two seconds, andthe first visual scan interval is from 10:00 am to 10:00:02 am, andsecond visual scan interval is from 10:00:03 am to 10:00:04 am, thenboth the visual scan intervals may be combined, and a combined visualscan interval is formed from 10:00 am to 10:00:04 am. According to athird pre-defined rule, the decision module 204 is configured to keep anitem from the scanned product list at a certain distance from the scaninterval, in order to cope with synchronization delays between thescanner and the video camera. The distance is the time between theborder of a visual scan interval and the moment given by the timestampof the scanned item. The decision module 204 is configured to correctsmall desynchronizations that are smaller than the pause between twoconsecutive scans. It may happen sometimes, that the due to high latencyof the network, the information about the scanned items may be delayed.In an example, the item may be actually scanned at 10:02 am but due tohigh latency, the timestamp of scanning of the item may be recorded as10:03 am. So, the decision module 204 takes into consideration of thissmall delay to validate/invalidate a detected visual scan interval, soas to maintain synchronization between the scanner and camera.

According to a fourth pre-defined rule, the decision module 204 isconfigured to validate/invalidate a detected visual scan interval basedon computation of a corresponding glass motion coverage. In the contextof the present disclosure, the glass motion coverage is a ratio betweena number of frames depicting the glass area of the scanning zone, andthe number of frames having a foreground other than the glass area, inthe scanning zone. The glass area is that area in the scanning zone thatcontains a glass that covers the scanner. The number of frames for whichthe glass motion coverage is computed could be around 10 frames for 25fps video stream. This is done so as to eliminate false positives due topassage of objects in the scanning zone, but without scanning intention.It is possible to have motion in the scanning zone, but outside theglass area (for example, head passing over some part of the scannerarea).

According to a fifth pre-defined rule, the decision module 204 isconfigured to validate/invalidate a detected visual scan interval basedon the percentage of skin pixels with respect to the foreground pixels.The decision module 204 may detect absence of a visual scan in a visualscan interval, when the percentage of skin pixels is larger than apre-defined skin pixel threshold value, as it indicates the presence ofempty hands in the scanning zone. Also, it may indicate that thecustomer has operated the scanning zone without the intention ofscanning. Thus, the decision module 204 invalidates corresponding visualscan interval, and does not use it for determining scan irregularity invisual scan detection

According to a sixth pre-defined rule, the decision module 204 isconfigured to invalidate a detected visual scan interval if an increasein corresponding number of key-points is less than a key-point thresholdvalue, as it indicates increase in number of key-points due to noise,and noise related misdetections. The decision module 204 invalidatescorresponding visual scan interval, and does not use it for determiningscan irregularity in visual scan detection.

The decision module 204 is configured to detect scan irregularity foreach validated visual scan interval, and generate an alert when the scanirregularity is detected. For example, the decision module 204 comparesan item of a validated visual scan interval with a list of scanned itemsgenerated for that interval. If the item of the validated visual scaninterval is not found in the list of items scanned by the scanner inthat interval, then the decision module 204 implies that there has beenan scan irregularity in visual scan detection. In an example, if thevideo camera detects that the product was present from 10:00 am to10:00:02 am in the scanning zone, however it is not present in the listof items scanned by the scanner from 10:00 am to 10:00:02 am, then thedecision module 204 infers that there is a scan irregularity in visualscan detection of the product. The decision module 204 is thenconfigured to generate an alert. The alert may be sent as an instantmessage or as email, or as a short message service, on the usercomputing devices, or at the display of corresponding self-checkoutterminals.

FIG. 3 is a flowchart illustrating a method 300 for generating an alertwhen there is a scan irregularity in visual scan detection in the retailenvironment 100, in accordance with an embodiment of the presentdisclosure. The order in which the method 300 is described is notintended to be construed as a limitation, and any number of thedescribed method blocks can be combined in any appropriate order tocarry out the method 300 or an alternative method. Additionally,individual blocks may be deleted from the method 300 without departingfrom the scope of the subject matter described herein.

At step 302, a video stream of a scanning zone in real-time is receivedfrom at least one video camera, wherein the scanning zone is a region ina field of view of a scanner of the retail store. At step 304, eachimage frame of the video stream is processed for detecting one or morevisual scan intervals in one or more image frames, wherein the visualscan interval is a time interval during which an item is identified inthe scanning zone for scanning by the scanner. In an embodiment of thepresent disclosure, the image processing includes detecting a scanaction in a current image frame based on presence of a human hand in thecurrent image frame, wherein the presence of a human hand is detectedbased on a percentage of skin pixels in the current image frame relativeto a previous image frame. The image processing further includesdetecting a scan action in the current image frame based on a movementof the human hand in the current image frame, wherein the motion isdetected based on a percentage of motion pixels in the current imageframe relative to the previous image frame. The image processing furtherincludes detecting a scan action in the current image frame based onpresence of an object in the human hand in the current image frame,wherein the presence of the object is determined based on a number ofkey-points in the scanning zone, wherein the key-point detector detectsa visual scan interval for the current image frame, if a scan action isfound in the current image frame.

At step 306, each detected visual scan interval is processed based on aset of pre-defined rules, wherein a processed visual scan intervalincludes a valid scan action, wherein the valid scan action is a useraction performed for scanning an item.

According to a first pre-defined rule, a pre-defined range of a visualscan interval is set, wherein the detected visual scan interval isinvalidated that is outside the pre-defined range of the visual scaninterval. According to a second pre-defined rule, a pre-definedthreshold distance is set, wherein the two consecutive visual scanintervals are merged, if a distance between the two consecutive visualscan intervals is less than the pre-defined threshold distance.According to a third pre-defined rule, a synchronization delay betweenthe video camera and the scanner is taken into account, while processinga visual scan interval. According to a fourth pre-defined rule, adetected visual scan interval is validated based on computation of aglass motion coverage in one or more corresponding image frames.According to a fifth pre-defined rule, a detected visual scan intervalis validated based on a percentage of skin pixels with respect toforeground pixels in corresponding image frames. According to a sixthpre-defined rule, a detected visual scan interval is invalidated if anumber of key-points in corresponding image frames is less than akey-point threshold value.

At step 308, a scan irregularity is detected in the check-out process,wherein the scan irregularity occurs when an item identified forscanning in a processed visual scan interval is absent in a list ofscanned items generated by the scanner during corresponding interval. Inan example, a user may bring up an item in the scanning zone of thescanner, but the user may hold the item in such a way that the bar codeof the item may not be visible to the bar code scanner. In such case,the user may put the item in their shopping bag after performing thescan action, but in reality, it may not be scanned by the scanner, andthe user may not receive a bill for that item. This leads to scanirregularity.

At step 310, an alert is provided regarding the scan irregularity at auser computing device. The alert may be sent as an instant message or asemail, or as a short message service, on the user computing devices, orat the display of corresponding self-checkout terminals.

Modifications to embodiments of the present disclosure described in theforegoing are possible without departing from the scope of the presentdisclosure as defined by the accompanying claims. Expressions such as“including”, “comprising”, “incorporating”, “consisting of”, “have”,“is” used to describe and claim the present disclosure are intended tobe construed in a non-exclusive manner, namely allowing for items,components or elements not explicitly described also to be present.Reference to the singular is also to be construed to relate to theplural.

1. A system for detecting a scan irregularity in scanning of one or moreitems by a user, during a check-out process at a retail store, thesystem comprising: an image receiving module configured to receive avideo stream of a scanning zone in real-time from at least one videocamera, wherein the scanning zone is a region in a field of view of ascanner of the retail store; an image processing module configured toprocess each image frame of the video stream for detecting one or morevisual scan intervals in one or more image frames, wherein the visualscan interval is a time interval during which an item is identified inthe scanning zone for scanning by the scanner; and a decision moduleconfigured to: process each detected visual scan interval based on a setof pre-defined rules, wherein a processed visual scan interval includesa valid scan action, wherein the valid scan action is a user actionperformed for scanning an item; detect a scan irregularity in thecheck-out process, wherein the scan irregularity occurs when an item isidentified for scanning in a processed visual scan interval is absent ina list of scanned items generated by the scanner during correspondinginterval; and provide an alert regarding the scan irregularity at a usercomputing device.
 2. The system of claim 1, wherein the image processingmodule comprises: a skin tone detector configured to detect a scanaction in a current image frame based on presence of a human hand in thecurrent image frame, wherein the presence of a human hand is detectedbased on a percentage of skin pixels in the current image frame relativeto a previous image frame; a motion detector configured to detect a scanaction in the current image frame based on a movement of the human handin the current image frame, wherein the motion is detected based on apercentage of motion pixels in the current image frame relative to theprevious image frame; and a key-point detector configured to detect ascan action in the current image frame based on presence of an object inthe human hand in the current image frame, wherein the presence of theobject is determined based on a number of key-points in the scanningzone, wherein the key-point detector detects a visual scan interval forthe current image frame, if a scan action is found in the current imageframe.
 3. The system of claim 1, wherein the decision module isconfigured to set a pre-defined range of a visual scan interval based ona first pre-defined rule, wherein the decision module invalidates adetected visual scan interval that is outside the pre-defined range ofthe visual scan interval.
 4. The system of claim 1, wherein the decisionmodule is configured to set a pre-defined threshold distance based on asecond pre-defined rule, wherein the decision module merges twoconsecutive visual scan intervals if a distance between the twoconsecutive visual scan intervals is less than the pre-defined thresholddistance.
 5. The system of claim 1, wherein the decision module isconfigured to take into account of a synchronization delay between thevideo camera and the scanner based on a third pre-defined rule, whileprocessing a visual scan interval.
 6. The system of claim 1, wherein thedecision module is configured to validate a detected visual scaninterval based on computation of a glass motion coverage in one or morecorresponding image frames, based on a fourth pre-defined rule.
 7. Thesystem of claim 1, wherein the decision module is configured to validatea detected visual scan interval based on a percentage of skin pixelswith respect to foreground pixels in corresponding image frames, basedon a fifth pre-defined rule.
 8. The system of claim 1, wherein thedecision module is configured to invalidate a detected visual scaninterval if a number of key-points in corresponding image frames is lessthan a key-point threshold value, based on a sixth pre-defined rule. 9.A method for detecting a scan irregularity in scanning of one or moreitems by a user, during check-out process at a retail store, the methodcomprising: receiving a video stream of a scanning zone in real-timefrom at least one video camera, wherein the scanning zone is a region ina field of view of a scanner of the retail store; processing each imageframe of the video stream for detecting one or more visual scanintervals in one or more image frames, wherein the visual scan intervalis a time interval during which an item is identified in the scanningzone for scanning by the scanner; processing each detected visual scaninterval based on a set of pre-defined rules, wherein a processed visualscan interval includes a valid scan action, wherein the valid scanaction is a user action performed for scanning an item; detecting a scanirregularity in the check-out process, wherein the scan irregularityoccurs when an item identified for scanning in a processed visual scaninterval is absent in a list of scanned items generated by the scannerduring corresponding interval; and providing an alert regarding the scanirregularity at a user computing device.
 10. The method of claim 9,wherein the processing each image frame of the video stream comprises:detecting a scan action in a current image frame based on presence of ahuman hand in the current image frame, wherein the presence of a humanhand is detected based on a percentage of skin pixels in the currentimage frame relative to a previous image frame; detecting a scan actionin the current image frame based on movement of the human hand in thecurrent image frame, wherein the motion is detected based on apercentage of motion pixels in the current image frame relative to theprevious image frame; and detecting a scan action in the current imageframe based on presence of an object in the human hand in the currentimage frame, wherein the presence of the object is determined based on anumber of key-points in the scanning zone, wherein the key-pointdetector detects a visual scan interval for the current image frame, ifa scan action is found in the current image frame.
 11. The method ofclaim 9 further comprising setting a pre-defined range of scan intervalbased on a first pre-defined rule, wherein a detected visual scaninterval is invalidated, that is outside the pre-defined range of scaninterval.
 12. The method of claim 9 further comprising setting apre-defined threshold distance based on a second pre-defined rule formerging two consecutive visual scan intervals if a distance between thetwo consecutive visual scan intervals is less than the pre-definedthreshold distance.
 13. The method of claim 9 further comprising takinginto account of a synchronization delay between the video camera and thescanner based on a third pre-defined rule, while processing a visualscan interval.
 14. The method of claim 9 further comprising validating adetected visual scan interval based on computation of a glass motioncoverage in one or more corresponding image frames, based on a fourthpre-defined rule.
 15. The method of claim 9 further comprisingvalidating a detected visual scan interval based on a percentage of skinpixels with respect to foreground pixels in corresponding image frames,based on a fifth pre-defined rule.
 16. The method of claim 9 furthercomprising invalidating a detected visual scan interval if a number ofkey-points in corresponding image frames is less than a key-pointthreshold value, based on a sixth pre-defined rule.
 17. A computerprogrammable product for detecting a scan irregularity in scanning ofone or more items by a user, during check-out process at a retail store,the computer programmable product comprising a set of instructions, theset of instructions when executed by a processor causes the processorto: receive a video stream of a scanning zone in real-time from at leastone video camera, wherein the scanning zone is a region in a field ofview of a scanner of the retail store; process each image frame of thevideo stream for detecting one or more visual scan intervals in one ormore image frames, wherein the visual scan interval is a time intervalduring which an item is identified in the scanning zone for scanning bythe scanner; process each detected visual scan interval based on a setof pre-defined rules, wherein a processed visual scan interval includesa valid scan action, wherein the valid scan action is a user actionperformed for scanning an item; detect a scan irregularity in thecheck-out process, wherein the scan irregularity occurs when an itemidentified for scanning in a processed visual scan interval is absent ina list of scanned items generated by the scanner during correspondinginterval; and provide an alert regarding the scan irregularity at a usercomputing device.
 18. The computer programmable product of claim 17,wherein the set of instructions when executed by a processor causes theprocessor to: detect a scan action in a current image frame based onpresence of a human hand in the current image frame, wherein thepresence of human hand is detected based on a percentage of skin pixelsin the current image frame relative to a previous image frame; detect ascan action in the current image frame based on movement of the humanhand in the current image frame, wherein the motion is detected based ona percentage of motion pixels in the current image frame relative to theprevious image frame; and detect a scan action in the current imageframe based on presence of an object in the human hand in the currentimage frame, wherein the presence of the object is determined based on anumber of key-points in the scanning zone, wherein the key-pointdetector detects a visual scan interval for the current image frame, ifa scan action is found in the current image frame.
 19. The computerprogrammable product of claim 17, wherein the set of instructions whenexecuted by a processor causes the processor to: set a pre-defined rangeof scan interval based on a first pre-defined rule, wherein the decisionmodule invalidates a detected visual scan interval that is outside thepre-defined range of scan interval; set a pre-defined threshold distancebased on a second pre-defined rule, wherein the decision module mergestwo consecutive visual scan intervals if a distance between the twoconsecutive visual scan intervals is less than the pre-defined thresholddistance; take into account of a synchronization delay between the videocamera and the scanner based on a third pre-defined rule, whileprocessing a visual scan interval; validate a detected visual scaninterval based on computation of a glass motion coverage in one or morecorresponding image frames, based on a fourth pre-defined rule; validatea detected visual scan interval based on a percentage of skin pixelswith respect to foreground pixels in corresponding image frames, basedon a fifth pre-defined rule; and invalidate a detected visual scaninterval if a number of key-points in corresponding image frames is lessthan a key-point threshold value, based on a sixth pre-defined rule.